CN113756970A

CN113756970A - Vehicle distribution device, vehicle distribution method, and recording medium

Info

Publication number: CN113756970A
Application number: CN202110582917.7A
Authority: CN
Inventors: 大八木大史; 高巢祐介; 永坂圭介; 金子智洋; 小笠原康二
Original assignee: Toyota Motor Corp
Current assignee: Toyota Motor Corp
Priority date: 2020-06-05
Filing date: 2021-05-27
Publication date: 2021-12-07
Anticipated expiration: 2041-05-27
Also published as: US20210380092A1; DE102021114118A1; CN113756970B

Abstract

The invention relates to a vehicle distribution device, a vehicle distribution method and a recording medium. So that it is possible to suppress a decrease in the performance of the internal combustion engine in the vehicle. The vehicle distribution device is provided with: a vehicle determination unit that determines, for each vehicle, a necessity to suppress a decrease in performance of the internal combustion engine based on vehicle information corresponding to the vehicle; a reservation determination unit that determines a reservation as a first reservation when reservation information corresponding to a reservation made by a vehicle satisfies a first condition for suppressing a decrease in performance to be expected; and a distribution unit that distributes the vehicle to the reservation based on the reservation information, wherein the distribution unit is capable of distributing the vehicle satisfying a second condition that is high in the necessity of suppressing the decrease in performance or the vehicle having a higher necessity of suppressing the decrease in performance than other vehicles to the reservation when the reservation is the first reservation.

Description

Vehicle distribution device, vehicle distribution method, and recording medium

Technical Field

The invention relates to a vehicle distribution device, a vehicle distribution method and a recording medium.

Background

As a related art, there is known a technique of burning particulate matter captured by a particulate trap by causing high-temperature exhaust gas to act on the particulate matter in a vehicle provided with the particulate trap in an exhaust passage of an internal combustion engine (for example, see patent document 1). According to this technique, accumulation of particulate matter in the particulate trap can be suppressed.

Further, in some cases, oil is diluted with water by condensation or the like in the internal combustion engine, and the lubrication performance may be degraded. On the other hand, a technique for recovering oil from a diluted state is known (for example, see patent document 2).

Documents of the prior art

Patent document

Patent document 1: japanese patent laid-open publication No. 2003-155915

Patent document 2: japanese laid-open patent publication No. 2015-168379

Disclosure of Invention

Problems to be solved by the invention

In such a vehicle that burns particulate matter, for example, when an operating state in which the load is relatively low continues in the internal combustion engine, the temperature of the exhaust gas is less likely to rise to the temperature at which the particulate matter burns. In such a case, combustion of the particulate matter by the exhaust gas is not promoted, and the accumulation amount of the particulate matter in the particulate trap may increase.

In addition, a state in which oil is diluted with water and deteriorates often occurs in a vehicle in which an internal combustion engine is intermittently operated, such as a hybrid vehicle or a plug-in hybrid vehicle.

Such a state in which the performance of the internal combustion engine is degraded, such as accumulation of particulate matter and degradation of oil, may occur in a vehicle sharing a system of a lending vehicle such as an automobile or a rental car.

The present invention has been made in view of the above circumstances, and an object thereof is to provide a vehicle distribution device, a vehicle distribution method, and a program that can suppress a decrease in performance of an internal combustion engine in a vehicle.

Means for solving the problems

In order to solve the above problems and achieve the object, a vehicle distribution device according to an aspect of the present invention includes: a vehicle determination unit that determines, for each vehicle, a necessity to suppress a decrease in performance of the internal combustion engine based on vehicle information corresponding to the vehicle; a reservation determination unit that determines a reservation as a first reservation when reservation information corresponding to a reservation of a borrowed vehicle satisfies a first condition that can suppress a decrease in performance; and a distribution unit that distributes a vehicle to the reservation based on the reservation information, wherein the distribution unit is capable of distributing a vehicle satisfying a second condition that indicates a high necessity of suppressing the decrease in the performance or a vehicle having a higher necessity of suppressing the decrease in the performance than other vehicles to the reservation when the reservation is the first reservation.

According to this configuration, the vehicle distribution device can distribute the vehicle with high necessity of suppressing the deterioration of the performance of the internal combustion engine to the first reservation where the suppression of the deterioration of the performance of the internal combustion engine is expected, and therefore the vehicle distribution device can suppress the deterioration of the performance of the internal combustion engine with respect to the reserved vehicle.

In addition, in the vehicle distribution device, the necessity of suppressing a decrease in performance of the internal combustion engine is a necessity of reducing particulate matter accumulated in a particulate trap provided in an exhaust path of the internal combustion engine.

According to this configuration, since the vehicle distribution device can distribute the vehicle with a high necessity of reducing the amount of the particulate matter stored in the vehicle to the first reservation where the amount of the particulate matter stored in the particulate trap can be expected to be reduced by combustion, the vehicle distribution device can suppress the accumulation of the particulate matter in the vehicle by distributing the particulate matter to the reserved vehicle.

In addition, in the vehicle distribution device, the necessity of suppressing the decrease in the performance of the internal combustion engine is a necessity of decreasing the degree of deterioration of the oil in the internal combustion engine.

According to this configuration, since the vehicle distribution device can distribute the vehicle with a high necessity of reducing the degree of degradation of the oil to the first reserved distribution where the degree of degradation of the oil in the internal combustion engine can be expected to be reduced, the oil in the internal combustion engine of the vehicle can be suppressed from being degraded by the distribution to the reserved vehicle.

The vehicle distribution device further includes a driver determination unit that determines the driver as the first driver when driver information corresponding to the driver satisfies a third condition that can suppress the performance degradation, and the reservation determination unit determines the reservation as the first reservation when the reservation is a reservation for driving the vehicle by the first driver.

According to this configuration, the vehicle distribution device can suppress the deterioration of the performance of the internal combustion engine in the vehicle with a higher probability because the vehicle distribution device can suppress the deterioration of the performance of the reserved distribution of driving to the driver who can expect the suppression of the deterioration of the performance of the internal combustion engine.

The driver information is information indicating the driving performance of the driver.

According to this configuration, the vehicle distribution device can determine whether or not the driver is a driver who can expect suppression of degradation of the performance of the internal combustion engine based on the traveling performance, and can suppress degradation of the performance of the internal combustion engine in the vehicle with a higher probability because the vehicle distribution device is a vehicle whose necessity for suppressing degradation of the performance of reservation distribution to the driver who determines that the degradation of the performance can be expected is high.

The reservation determination unit determines the driver as the first driver when driver information corresponding to the driver included in the reservation information satisfies a third condition that can suppress the performance degradation, and determines the reservation as the first reservation when the reservation is a reservation for driving the vehicle by the first driver.

With this configuration, the reservation determination unit can determine the first driver based on the reservation information, and suppress a decrease in performance of the internal combustion engine in the vehicle.

In addition, in the vehicle distribution device, the reservation determination section determines whether or not the reservation is the first reservation based on the scheduled route information included in the reservation information.

According to this configuration, the vehicle distribution device can determine whether the reservation is the first reservation in which the suppression of the decrease in the performance of the internal combustion engine can be expected based on the scheduled route information, and distribute the vehicle with high necessity of suppressing the decrease in the performance to the first reservation, so it is possible to suppress the decrease in the performance of the internal combustion engine in the vehicle with a higher probability.

In the vehicle distribution device, the reservation determination unit may determine the reservation as the first reservation when the planned route information includes a predetermined road as a planned travel route or a point separated by a predetermined distance from a reference position as a planned route point.

According to this configuration, the vehicle distribution device can determine whether the reservation is the first reservation in which the suppression of the decrease in the performance of the internal combustion engine can be expected, based on the scheduled travel route and the scheduled route point, and distribute the vehicle with high necessity of suppressing the decrease in the performance to the first reservation, so that the decrease in the performance of the internal combustion engine can be suppressed with a higher probability.

In the vehicle distribution device, the reservation determination unit may predict a traveling pattern of the vehicle based on the reservation information, and determine the reservation as the first reservation when information indicating the traveling pattern satisfies a fourth condition that can suppress the performance degradation.

With this configuration, the vehicle distribution device can determine whether the reservation is the first reservation in which the suppression of the degradation of the performance of the internal combustion engine can be expected based on the traveling mode predicted from the reservation information, and distribute the vehicle with high necessity of suppressing the degradation of the performance to the first reservation, so that the degradation of the performance of the internal combustion engine in the vehicle can be suppressed with a higher probability.

In the vehicle distribution device, the reservation determination unit may predict a traveling pattern of the vehicle based on the reservation information and driver information corresponding to a driver who drives the vehicle in the reservation.

According to this configuration, the vehicle distribution device can determine whether the reservation is the first reservation in which the suppression of the degradation of the performance of the internal combustion engine can be expected, based on the traveling pattern of the driver predicted from the reservation information and the driver information, and distribute the vehicle with high necessity of suppressing the degradation of the performance to the first reservation, so that the degradation of the performance of the internal combustion engine in the vehicle can be suppressed with a higher probability.

In the vehicle distribution device, the information indicating the traveling pattern may be at least one of information indicating a predicted average speed, information indicating a predicted traveling distance, information indicating a predicted traveling time, a predicted load of the internal combustion engine, and information indicating a predicted number of accelerations.

According to this configuration, the vehicle distribution device can determine whether the reservation is the first reservation in which the suppression of the degradation of the performance of the internal combustion engine can be expected based on the average speed, the travel distance, the travel time, the predicted load of the internal combustion engine, and the number of accelerations predicted from the reservation information, and can distribute the vehicle with high necessity of suppressing the degradation of the performance to the first reservation.

In addition, a vehicle distribution method according to an aspect of the present invention is a computer-implemented vehicle distribution method including: determining a necessity of suppressing a decrease in performance of the internal combustion engine for each vehicle based on vehicle information corresponding to the vehicle read out from the storage unit; a step of determining that the reservation is the first reservation when reservation information corresponding to the reservation satisfies a first condition that can suppress the performance degradation; and a step of allocating a vehicle to the reservation based on the reservation information, wherein in the step of allocating a vehicle to the reservation, when the reservation is the first reservation, a vehicle satisfying a second condition that the necessity of suppressing the decrease in the performance is high or a vehicle whose necessity of suppressing the decrease in the performance is higher than that of another vehicle can be allocated to the reservation.

According to such a method, since a vehicle having a high necessity of suppressing the decrease in performance can be allocated to the first reservation where the decrease in performance of the internal combustion engine can be predicted, the decrease in performance of the internal combustion engine in the vehicle can be suppressed by allocating to the reserved vehicle.

A program according to an aspect of the present invention is a program causing a computer to function as a vehicle determination unit that determines, for each vehicle, a necessity of suppressing a decrease in performance of an internal combustion engine based on vehicle information corresponding to the vehicle, a reservation determination unit that determines a reservation as a first reservation when reservation information corresponding to the reservation satisfies a first condition that can suppress the decrease in performance, and a distribution unit that distributes the vehicle to the reservation based on the reservation information, wherein the distribution unit is capable of distributing, to the reservation, a vehicle that satisfies a second condition that is higher in the necessity of suppressing the decrease in performance or a vehicle that is higher in the necessity of suppressing the decrease in performance than other vehicles when the reservation is the first reservation.

According to such a program, since a vehicle having a high necessity of suppressing the decrease in performance can be allocated to the first reservation where the decrease in performance of the internal combustion engine can be predicted, the decrease in performance of the internal combustion engine in the vehicle can be suppressed by allocating the vehicle to the reserved vehicle.

Effects of the invention

According to the vehicle distribution device, the vehicle distribution method, and the program of the present invention, it is possible to suppress a decrease in performance of the internal combustion engine in the vehicle by distribution to the reserved vehicle.

Drawings

Fig. 1 is an exemplary configuration diagram of a shared automobile system including a vehicle distribution device according to an embodiment.

Fig. 2 is an exemplary block diagram of a shared automobile system including the vehicle distribution device according to the embodiment.

Fig. 3 is an exemplary block diagram of the control unit and the storage unit of the vehicle distribution device according to the first embodiment.

Fig. 4 is an exemplary flowchart showing the procedure of determining the necessity of reduction of particulate matter for each vehicle by the vehicle distribution device of the first embodiment.

Fig. 5 is an exemplary flowchart showing the procedure of driver determination performed by the vehicle distribution device of the first embodiment.

Fig. 6 is an exemplary flowchart showing steps of determining a reservation and allocating a vehicle to the reservation by the vehicle allocation device of the first embodiment.

Fig. 7 is an illustrative flowchart showing the procedure of determining the necessity of reduction in the degree of oil degradation for each vehicle by the vehicle distribution device of the second embodiment.

Fig. 8 is an exemplary block diagram of a control unit and a storage unit of the vehicle distribution device according to the third embodiment.

Fig. 9 is an exemplary schematic diagram showing a configuration of a neural network learned by a learning unit of the vehicle distribution device according to the third embodiment.

Fig. 10 is an exemplary explanatory diagram of input and output at nodes included in the neural network according to the third embodiment.

Description of the reference symbols

10. 10A … server (vehicle distribution device)

12d … vehicle determination unit

12g … driver determination unit

12i … reservation determination unit

12j … distribution part

13 … storage part

20 … vehicle

20a … internal combustion engine

20b … exhaust path

20c … particle catcher

Detailed Description

Hereinafter, exemplary embodiments of the present invention are disclosed. The structure of the embodiment described below and the operation and result (effect) of the structure are examples. The present invention can be realized by other configurations than those disclosed in the following embodiments. In addition, according to the present invention, at least one of various effects (including an effect of an epistatic property) obtained by the following configuration can be obtained.

The embodiments described below have the same configuration. Thus, according to the configurations of the respective embodiments, the same operation and effects can be obtained by the same configurations. In the following, the same components are denoted by the same reference numerals, and redundant description thereof is omitted.

In the present specification, ordinal numbers are given for convenience in order to distinguish conditions, reservations, drivers, vehicles, and the like, and do not indicate priority and order. The "information" represents the value and data of the parameter, and the "accumulation of particulate matter" represents the accumulation of particulate matter in the particulate trap.

[ first embodiment ]

[ System Structure ]

Fig. 1 is a block diagram of a shared automobile system 1. As shown in fig. 1, the shared automobile system 1 includes a server 10, a vehicle 20, and a terminal 30.

The server 10 is a computer and executes a so-called vehicle allocation process, which is a process of allocating any one of the plurality of vehicles 20 to a reservation of the vehicle 20 from the terminal 30. The server 10 is an example of a vehicle distribution device.

At least a part of the vehicles 20 includes an internal combustion engine 20a whose operating state changes in accordance with a driving operation of the vehicle 20 by a driver, and a particulate trap 20c provided in an exhaust passage 20b of the internal combustion engine 20a and configured to trap particulate matter contained in exhaust gas. The internal combustion engine 20a is a drive source of the vehicle 20 such as a gasoline engine or a diesel engine. The vehicle 20 may be provided with a rotating electric machine as a drive source in addition to the internal combustion engine 20 a. The internal combustion engine 20a may not be a drive source of the vehicle 20, and may be an internal combustion engine that rotates by a generator that compensates for drive power of a rotating electric machine as a drive source of the vehicle 20.

The user sharing the automobile system 1 can reserve borrowing of the vehicle 20 via the terminal 30. The terminal 30 is an electronic device such as a smartphone, a tablet, or a personal computer.

The server 10, the vehicle 20, and the terminal 30 can communicate data representing various information in accordance with a predetermined communication protocol via a communication network 40 including a wired or wireless communication line. The communication network 40 is also called an electric communication line or a computer network, and can take various forms.

Fig. 2 is a block diagram of the shared automobile system 1. As shown in fig. 2, the server 10 includes a communication unit 11, a control unit 12, a storage unit 13, and an input/output unit 14.

The communication unit 11 communicates data with the vehicle 20 and the terminal 30. The input/output unit 14 includes input devices such as a keyboard, a mouse, and a touch panel, and output devices such as a display and a speaker. The input/output unit 14 is a user interface for an administrator or an operator who shares the automobile system 1. The control unit 12 and the storage unit 13 of the server 10 will be described in detail later.

The vehicle 20 includes a communication unit 21, a control unit 22, a storage unit 23, and a plurality of sensors 24. The communication unit 21 communicates data with the server 10 and the terminal 30.

The control unit 22 is a computer and includes a processor (circuit) such as a CPU (central processing unit), and a main memory unit such as a RAM (random access memory) or a ROM (read only memory). The control unit 22 is, for example, an MCU (micro controller unit). The storage unit 23 includes a nonvolatile storage device such as an SSD (solid state drive) or an HDD (hard disk drive). The storage unit 23 can also be referred to as an auxiliary storage device. The control unit 22 and the storage unit 23 are included in, for example, an ECU (electronic control unit).

The processor reads a program stored in the ROM or the storage unit 23 and executes each process. The program is a file in an installable format or an executable format, and can be recorded on a computer-readable recording medium and provided. The recording medium can also be referred to as a program product. The program and information such as values, tables, and maps used for the arithmetic processing by the processor may be stored in advance in the ROM or the storage unit 23, or may be stored in a storage unit of a computer connected to a communication network, and downloaded via the communication network to be stored in the storage unit 23. The

storage sections

13 and 23 store data written by the processor. The arithmetic processing of the control unit 22 may be at least partially executed by hardware. In this case, the control unit 22 includes, for example, an FPGA (field programmable gate array), an ASIC (application specific integrated circuit), and the like.

The sensor 24 detects various physical quantities related to the running of the vehicle 20 and the operation of the internal combustion engine 20a, respectively. The sensor 24 includes a sensor 24 that detects various physical quantities related to the generation of particulate matter in the internal combustion engine 20a and the combustion of particulate matter in the particulate trap 20 c. Such a sensor 24 is, for example, a sensor that detects the speed of the vehicle 20, a sensor that detects the acceleration of the vehicle 20, a sensor that detects the amount of operation of an accelerator pedal, a sensor that detects the rotational speed of the internal combustion engine 20a, a sensor that detects the temperature of the particulate trap 20c or the temperature of the exhaust gas of the internal combustion engine 20a, a sensor that detects the intake air flow rate, a sensor that detects the differential pressure before and after the particulate trap 20c, or the like. A GPS (global positioning system) capable of acquiring the time and the position of the vehicle 20 is also an example of the sensor 24.

The control unit 22 can calculate a value (hereinafter, referred to as a calculated value) related to the generation of the particulate matter in the internal combustion engine 20a and the combustion of the particulate matter in the particulate trap 20c based on the detection value detected by the sensor 24.

The control unit 22 can write the detected value and the calculated value in the storage unit 23. In other words, the storage unit 23 can store the detection value of the sensor 24 and a calculated value based on the detection value. The control unit 22 may control the communication unit 21 to transmit the detected value and the calculated value to the server 10.

The terminal 30 includes a communication unit 31, a control unit 32, a storage unit 33, and an input/output unit 34.

The communication unit 31 communicates data with the server 10 or the vehicle 20. The input/output unit 34 includes input devices such as a keyboard, a mouse, and a touch panel, and output devices such as a display and a speaker. The input/output unit 34 is a user interface for a user (reservation user) who shares the automobile system 1.

The control unit 32 is a computer and includes a processor (circuit) such as a CPU, and main storage units such as a RAM and a ROM. The storage unit 33 includes a nonvolatile storage device such as an SSD or an HDD. The storage unit 33 can also be referred to as an auxiliary storage device.

The processor reads a program stored in the ROM or the storage unit 33 and executes each process. The program is a file in an installable format or an executable format, and can be recorded on a computer-readable recording medium and provided. The recording medium can also be referred to as a program product. The program and information such as values, tables, and maps used for the arithmetic processing by the processor may be stored in advance in the ROM and the storage unit 33, or may be stored in a storage unit of a computer connected to a communication network, and downloaded via the communication network to be stored in the storage unit 33. The storage section 33 stores data written by the processor. The arithmetic processing of the control unit 32 may be at least partially executed by hardware. In this case, the control unit 32 includes, for example, an FPGA, an ASIC, and the like.

The control unit 32 operates an application program (program, hereinafter referred to as reservation application) that executes a reservation for the shared vehicle 20 in the automobile system 1. The reservation application is configured as an independent operation application or a web application. The control unit 32 acquires information input from the input/output unit 34 by reserving the operation of the application. The control unit 32 controls the communication unit 31 to transmit the information input from the input/output unit 34 to the server 10 by the operation of the reservation application, and controls the communication unit 31 to receive the information transmitted from the server 10 to the terminal 30. Further, the control unit 32 displays and outputs information obtained from the server 10 at the input/output unit 34 or outputs voice by the operation of the reservation application.

The information input from the input/output unit 34 includes reservation information indicating a request for a reservation with the use of the automobile 20. The reservation information includes, for example, information indicating the driving (borrowing) start time, the driving start point, the driving (borrowing) end time, the driving end point, a scheduled route point (including a destination), a scheduled travel route, the presence or absence of use of an expressway, attribute information of the driver, and the like, in addition to the identification information of the driver.

[ Structure and operation of Server ]

Fig. 3 is a block diagram of the control unit 12 and the storage unit 13 of the server 10. As shown in fig. 3, the control unit 12 includes a vehicle information acquisition unit 12a, a reservation information acquisition unit 12b, a driver information acquisition unit 12c, a vehicle determination unit 12d, a vehicle information update unit 12e, a driver information update unit 12f, a driver determination unit 12g, a travel pattern prediction unit 12h, a reservation determination unit 12i, and an assignment unit 12 j. The storage unit 13 includes a driver information database 13a for storing driver information and a vehicle information database 13b for storing vehicle information. In fig. 3, the database is described as DB.

The control unit 12 is a computer and includes a processor (circuit) such as a CPU, and main storage units such as a RAM and a ROM. The storage unit 13 includes a nonvolatile storage device such as an SSD or an HDD. The storage unit 13 can also be referred to as an auxiliary storage device.

The processor reads out and executes programs stored in the ROM and the storage unit 13, and operates as a vehicle information acquisition unit 12a, a reservation information acquisition unit 12b, a driver information acquisition unit 12c, a vehicle determination unit 12d, a vehicle information update unit 12e, a driver information update unit 12f, a driver determination unit 12g, a traveling pattern prediction unit 12h, a reservation determination unit 12i, and a distribution unit 12 j. The program is a file in an installable format or an executable format, and can be recorded on a computer-readable recording medium and provided. The recording medium can also be referred to as a program product. The program and information such as values, tables, and maps used for the arithmetic processing of the processor may be stored in advance in the ROM and the storage unit 13, or may be stored in a storage unit of a computer connected to a communication network, and downloaded via the communication network to be stored in the storage unit 13. The storage section 13 stores data written by the processor. The arithmetic processing of the control unit 12 may be at least partially executed by hardware. In this case, the control unit 12 includes, for example, an FPGA, an ASIC, and the like.

The driver information database 13a stores driver information so as to be associated with identification information of the driver. That is, the driver information is information associated with the identification information of the driver. The driver information includes, for example, information indicating an average speed, a travel distance, a travel time, the number of accelerations equal to or higher than a predetermined acceleration, and an average acceleration during acceleration as information indicating the travel performance of the driver. The driver information includes information related to accumulation of particulate matter. The information related to accumulation of the particulate matter is, for example, classification of the driver who has a high possibility of performing driving with a reduced amount of accumulation of the particulate matter, a change amount of the amount of accumulation of the particulate matter due to driving of the driver, and the like, as described later. The driver information includes attribute information indicating an attribute of the driver. Accumulation of particulate matter is an example of a factor that reduces the performance of the internal combustion engine 20 a.

In addition, the vehicle information database 13b stores vehicle information so as to be associated with the identification information of the vehicle 20. That is, the vehicle information is information associated with the identification information of the vehicle 20. The vehicle information includes, for example, a map, a table, a coefficient of a function, and the like set for each vehicle 20 or vehicle type for calculating the accumulation amount and the change amount of the particulate matter based on the detection value of the sensor 24, in addition to the accumulation amount of the particulate matter in each vehicle 20 calculated based on the detection value of the sensor 24, as information related to accumulation of the particulate matter in each vehicle 20. The vehicle information may include a detection value of the sensor 24 during the past travel of the vehicle 20 and a change with time of a calculated value based on the detection value. The vehicle information includes a classification, a level, and a value indicating a necessity of reduction of the particulate matter (hereinafter, referred to as a necessity of reduction). The vehicle information includes attribute information of the vehicle such as the size (level), the driver, and the type of each vehicle 20. The storage unit 23 of each vehicle 20 may store a map, a table, a coefficient of a function, and the like for calculating the accumulation amount and the change amount of the particulate matter from the detected values.

The vehicle information acquiring unit 12a acquires the vehicle information of each vehicle 20 from the vehicle 20 or the vehicle information database 13 b.

The reservation information acquiring unit 12b acquires information related to reservation of the vehicle 20 (hereinafter, referred to as reservation information) from the terminal 30.

The driver information acquiring unit 12c acquires the driver information from the vehicle 20 or the driver information database 13 a.

[ vehicle determination ]

The vehicle determination section 12d determines the necessity of reduction in the particulate trap 20c of each vehicle 20. The necessity of reduction is an example of the necessity of suppressing the decrease in the performance of the internal combustion engine 20 a.

Fig. 4 is a flowchart showing a processing procedure of the determination of the necessity of reduction by the vehicle determination unit 12 d. The processing shown in fig. 4 can be executed at various timings, such as a point in time immediately after the vehicle 20 is returned, a point in time when the vehicle 20 becomes a candidate for allocation to a reservation (a point in time before allocation), and a predetermined point in time that is periodically set. In fig. 4, the particulate matter is denoted as PM.

Before the determination of the vehicle 20 by the vehicle determination unit 12d, the vehicle information acquisition unit 12a acquires the vehicle information corresponding to the vehicle 20 from at least one of the vehicle 20 and the vehicle information database 13b (S11). For example, the vehicle information acquisition unit 12a acquires the change with time of the detection value of the sensor 24 from the vehicle 20, and acquires, from the vehicle information database 13b, a map, a table, a coefficient of a function, and the like for calculating the increase amount and the decrease amount of the particulate matter based on the detection value in addition to the accumulation amount of the particulate matter in the vehicle 20.

Next, the vehicle determination unit 12d obtains the accumulation amount of particulate matter in the vehicle 20 based on the vehicle information obtained in S11 (S12).

In S12, the vehicle determination unit 12d can perform a calculation to estimate the accumulation amount of the particulate matter based on the vehicle information acquired in S11. By way of example, the following results were found: the amount of increase per unit time in the accumulation amount of particulate matter varies depending on the load of the internal combustion engine 20a and the rotation speed of the internal combustion engine 20 a. In addition, it was ascertained that: the amount of decrease per unit time of the particulate matter caused by the combustion of the particulate trap 20c varies depending on the temperature of the particulate trap 20c and the flow rate of the exhaust gas of the internal combustion engine 20 a. Also, the load of the internal combustion engine 20a can be represented by the operation amount of the accelerator pedal, and the flow rate of exhaust gas can be represented by the flow rate of intake air of the internal combustion engine 20 a. Then, at S11, the vehicle information obtaining unit 12a obtains the secular changes of the accelerator pedal operation amount, the rotation speed of the internal combustion engine 20a, the temperature of the particulate trap 20c, and the flow rate of the intake air from the secular change of the detection value of the vehicle 20 as the sensor 24 within a predetermined period. Here, the predetermined period is a period in which the amount of increase or decrease of the particulate matter in the particulate trap 20c after the time point at which the accumulation amount of the particulate matter has been calculated is calculated, and is, for example, a period from the start to the end (return) of lending of the vehicle 20 in the shared automobile. In S11, the vehicle information acquisition unit 12a acquires, from the vehicle information database 13b or the vehicle 20, a map (hereinafter referred to as an increase map) indicating the correlation between the accelerator pedal operation amount corresponding to the vehicle 20 and the rotation speed of the internal combustion engine 20a and the amount of increase per unit time of the particulate matter, and a map (hereinafter referred to as a decrease map) indicating the correlation between the temperature of the exhaust gas and the flow rate of the intake air corresponding to the vehicle 20 and the amount of decrease per unit time of the particulate matter. Then, at S11, the vehicle information obtaining unit 12a obtains the accumulation amount of particulate matter (hereinafter referred to as the residual amount Qp) of the vehicle 20 until the predetermined period from the vehicle information database 13b or the vehicle 20 as the vehicle information. Next, at S12, the vehicle determination unit 12d calculates the amount of increase Δ Qi of particulate matter in the particulate trap 20c within the predetermined period, based on the information indicating the secular changes in the accelerator pedal operation amount and the rotation speed of the internal combustion engine 20a within the predetermined period and the increase map. The vehicle determination unit 12d calculates the amount of decrease Δ Qd in the particulate matter in the particulate trap 20c during the predetermined period based on information indicating temporal changes in the exhaust gas temperature and the intake air flow rate during the predetermined period and a decrease map. Thus, the vehicle determination unit 12d can calculate the accumulation amount Q of the particulate matter at the current time point (in other words, after a predetermined period of time has elapsed) by the following equation (1).

Q＝Qp+ΔQi-ΔQd … (1)

As another example, when the vehicle 20 includes, as the sensor 24, a sensor 24 for detecting an intake air flow rate and a sensor 24 for detecting a differential pressure between the front and rear of the particulate trap 20c, the control unit 22 of the vehicle 20 can acquire the accumulation amount Q at any time based on detection values of these sensors 24, for example, on the basis of a mathematical expression or a map indicating a correlation between the detection value of the sensor 24 and the accumulation amount Q. In this case, in S12, the vehicle determination unit 12d can acquire the accumulation amount Q of the particulate matter at a predetermined time point (for example, the lending end time point (return time point) of the vehicle 20 in the shared automobile) from the vehicle information acquired in S11. The calculation of the accumulation amount Q of particulate matter based on the intake air flow rate and the differential pressure before and after the particulate trap 20c may be performed by the vehicle determination unit 12d based on the vehicle information acquired in S11.

Next, in S13, the vehicle determination unit 12d determines the necessity of reduction for each vehicle 20 based on the acquired accumulation amount Q of particulate matter. For example, the vehicle determination unit 12d may determine that the vehicle 20 is a vehicle with a high necessity of reduction when the accumulation amount Q is equal to or greater than a predetermined threshold value, and determine that the vehicle 20 is a vehicle with a low necessity of reduction when the accumulation amount Q is smaller than the predetermined threshold value. The predetermined threshold value can be set for each vehicle 20 or vehicle type, for example. The second condition is exemplified by the accumulation amount Q being equal to or larger than a predetermined threshold. As another example, the vehicle determination unit 12d can calculate the amount of change per unit length of the travel distance of the vehicle 20 of the accumulation amount Q from the past results of the accumulation amount Q, and further calculate the travel distance (delay distance) until the maximum allowable accumulation amount is reached, and determine the necessity of reduction based on the delay distance. In this case, the vehicle determination unit 12d may determine that the vehicle 20 is a vehicle with a high necessity of reduction when the delay distance is equal to or less than the corresponding threshold distance, and may determine that the vehicle 20 is a vehicle with a low necessity of reduction when the delay distance is longer than the threshold distance. The second condition is an example when the delay distance is equal to or less than the corresponding threshold distance. As another example, a plurality of divisions (levels) corresponding to the necessity of reduction may be set based on the accumulation amount Q, the delay distance, other parameters corresponding to the accumulation amount Q, and the like, and the vehicle determination unit 12d may determine the level of each vehicle 20 in S13. As another example, a parameter indicating the necessity of reduction as a numerical value may be set, and the vehicle determination unit 12d may calculate the value of the parameter in S13. The parameter is set to be larger as the delay distance is shorter, for example, and a larger value indicates a higher necessity of reduction. The control unit 12 associates information indicating the necessity of reduction for each vehicle 20 with the identification information of the vehicle 20 and writes the information into the storage unit 13.

After S12 or S13, the vehicle information update unit 12e rewrites the vehicle information of the vehicle information database 13b (S14).

[ driver judgment ]

The driver determination unit 12g shown in fig. 3 determines whether or not the driver is likely to perform a driving (hereinafter, referred to as a reduced driving) in which the amount of particulate matter accumulated in the particulate trap 20c is reduced.

Fig. 5 is a flowchart showing a processing procedure of the driver determination by the driver determination unit 12 g. The processing shown in fig. 5 can be executed at various timings, for example, at a point in time immediately after the vehicle 20 is returned, at a point in time when the vehicle 20 becomes a candidate for allocation to a reservation (a point in time before allocation), at a predetermined point in time that is set periodically, and the like.

Before the driver determination by the driver determination unit 12g, the driver information acquisition unit 12c acquires the driver information from the driver information database 13a or from the vehicle 20 and the driver information database 13a (S21). For example, in S21, the driver information acquisition unit 12c acquires the change with time of the detection value of the sensor 24 from the vehicle 20 within a predetermined period and the travel time of the vehicle 20 within the predetermined period. Here, the detection value of the sensor 24 is, for example, the speed, acceleration, travel distance, and the like of the vehicle 20. The predetermined period is a period after the time point at which the driver information is updated, and is, for example, a period from the start to the end (return) of lending of the vehicle 20 in the shared automobile. The driver information acquiring unit 12c acquires, from the driver information database 13a, an average speed, a travel distance, a travel time, the number of accelerations equal to or higher than a predetermined acceleration, and an average acceleration during acceleration as an actual result of the driving of the driver.

Next, the driver information update unit 12f calculates an average speed, a travel distance, a travel time, the number of accelerations equal to or greater than a predetermined acceleration, and an average acceleration during acceleration, which are obtained by adding a predetermined period to the past performance period, based on the driver information acquired from the vehicle 20 and the driver information database 13a, and stores these as new driver information in the driver information database 13a, that is, rewrites the calculated values (S22). When the driver information is updated, the driver information obtaining unit 12c obtains the average speed, the travel distance, the travel time, the number of accelerations equal to or higher than the predetermined acceleration, and the average acceleration during acceleration, which are the actual results of the driving of the driver, from the driver information database 13a as the driver information in S21, and S22 is omitted.

Next, the driver determination unit 12g determines whether or not the driver is a driver who has a high possibility of performing the reduced driving, based on the driver information acquired in S21 or the driver information updated in S22 (S23). In S23, the driver determination unit 12g determines that the driver is a driver who has a high possibility of performing the reduced driving when the driver information indicating the driving performance of the driver satisfies a predetermined condition (an example of a third condition) that can be expected to reduce the accumulation amount of the particulate matter by the driving. Hereinafter, in the first embodiment, a driver who has a high possibility of performing driving with a reduced accumulation amount of particulate matter is referred to as a first driver.

In S23, the driver determination unit 12g can determine the driver as the first driver when the average speed is equal to or greater than the corresponding threshold speed, the travel distance is equal to or greater than the corresponding threshold distance, or the travel time is equal to or greater than the corresponding threshold time, for example. As another example, the driver determination unit 12g may determine that the driver is the first driver when the number of accelerations equal to or greater than the predetermined acceleration is equal to or greater than the corresponding threshold number of accelerations or when the average acceleration during acceleration is equal to or greater than the corresponding threshold acceleration. The control unit 12 associates information indicating whether or not the driver is the first driver with the identification information of the driver and writes the information into the driver information database 13 a.

As another example, in S23, the driver determination unit 12g may determine whether or not the driver is the first driver based on the amount of change in the accumulation amount of the particulate matter caused by the driving performance of the driver. In this case, the driver information obtaining unit 12c obtains the amount of change in the accumulation amount of the particulate matter within a predetermined period, for example, after S12 in fig. 4 (or after S11 when the accumulation amount of the particulate matter is obtained from the vehicle 20), and obtains the travel time or the travel distance within the predetermined period (S21). In this case, the sign of the amount of change in the accumulation amount is positive when increasing, and negative when decreasing. Next, the driver information update unit 12f calculates the amount of change in the accumulation amount of the particulate matter and the travel distance or the travel time until the end of the predetermined period in which the predetermined period is added to the past performance based on the driver information acquired from the vehicle 20 and the driver information database 13a, and stores, that is, rewrites, the amount of change in the accumulation amount of the particulate matter and the travel distance or the travel time as new driver information in the driver information database 13a (S22). Then, the driver determination unit 12g determines that the driver is the first driver when the amount of change in the travel distance per unit length of the accumulation amount of the particulate matter is equal to or less than the corresponding threshold value or when the amount of change in the travel time per unit time of the accumulation amount of the particulate matter is equal to or less than the corresponding threshold value (S23). In this case, the control unit 12 also associates information indicating whether or not the driver is the first driver with the identification information of the driver and writes the information into the driver information database 13 a.

[ reservation determination and allocation of vehicles to reservations ]

The reservation judging section 12i shown in fig. 3 judges whether or not the reservation satisfies a condition (an example of the first condition) that can predict reduction of the particulate matter based on the reservation information acquired from the terminal 30. The traveling pattern prediction unit 12h predicts the traveling pattern of the vehicle 20 based on the reservation information. The distribution unit 12j selects a vehicle 20 that satisfies a condition (reservation condition) specified by the reservation information from the vehicles 20 managed by the shared automobile system 1, and distributes the vehicle 20 to the reservation. In the first embodiment, the reservation in which reduction of particulate matter is expected, that is, the reservation in which the possibility of reduction of driving is high, will be referred to as a first reservation hereinafter as an example.

Fig. 6 is a flowchart showing a processing procedure of reservation determination by the reservation determination unit 12i and allocation of the vehicle 20 to the reservation by the allocation unit 12 j. First, the reservation judging unit 12i acquires reservation information from the terminal 30 (S101). Next, the reservation judging unit 12i refers to the driver information database 13a to check whether or not the driver included in the reservation information is the first driver (S102). When the driver is the first driver (yes in S102), the reservation determination unit 12i determines the reservation as the first reservation (S107).

If no in S102, the reservation determination unit 12i determines that the reservation is the first reservation if the reservation information includes information on a planned travel route and the planned travel route is a predetermined road (yes in S103) (S107). The predetermined road is, for example, a road having a maximum speed of not less than a predetermined speed (for example, 50 km/h), such as an expressway, a vehicle-only road, and a high-specification road, in other words, a road on which traveling at a relatively high speed is possible. This is because, when the vehicle 20 travels at a relatively high speed, there is a high possibility that the driving is reduced. The predetermined road may be a road or a section of the road, which is registered in advance, such as a road having a section in which an ascending gradient equal to or larger than a predetermined value is continuously formed by a predetermined length, or the section. This is because, when the vehicle 20 climbs a slope on a slope with a relatively large gradient, there is a high possibility of reducing driving. As in this case, the reservation judging unit 12i may judge the predetermined road for each traffic direction. The information indicating the scheduled travel route is an example of the scheduled route information.

In the case of no in S103, if the reservation information includes the scheduled route position or the scheduled arrival position and the scheduled route position or the scheduled arrival position is separated from the reference position by a predetermined distance (for example, 50km) or more (yes in S104), the reservation determination unit 12i determines the reservation as the first reservation (S107). The predetermined arrival position is, for example, the farthest destination in the trip, and the reference position is, for example, a standby position, a storage position, a lending start position, a lending end position, and the like of the vehicle 20. This is because, when the vehicle is scheduled to travel to a relatively distant place, the speed of the vehicle 20 is likely to be high, and the possibility of reducing driving is high. The information indicating the scheduled route position or the scheduled arrival position is an example of the scheduled route information.

When the server 10 has a navigation function, the travel pattern prediction unit 12h can predict the travel pattern of the vehicle 20 such as a travel route, a travel road, an average speed, a travel distance, a travel time, and the number of accelerations from the information of the destination and the route point included in the reservation information. The traveling pattern prediction unit 12h can also predict the traveling pattern of the vehicle 20 based on the driving of the driver with higher accuracy, based on the driver information indicating the actual driving performance of the driver corresponding to the identification information of the driver included in the reservation information. The driver information indicating the actual performance of the driver's driving includes, for example, an average speed, a travel distance, a travel time, the number of accelerations equal to or higher than a predetermined acceleration, an average acceleration during acceleration, and the like. In this case, the travel pattern prediction unit 12h can predict the traffic on the expressway when the average speed in the actual results of driving is higher than the corresponding threshold value, predict the traffic on the ordinary road other than the expressway when the ratio of the travel time calculated from the actual results of driving to the travel distance is longer than the corresponding threshold value, predict the frequency of acceleration equal to or higher than the predetermined acceleration as the number of times of acceleration equal to or higher than the predetermined acceleration in the actual results of driving is larger, and predict that the vehicle will accelerate at the average acceleration at the time of acceleration in the actual results of driving.

If no in S104 and the traveling pattern prediction unit 12h predicts the traveling pattern of the vehicle 20 as described above (yes in S105), and if the information indicating the traveling pattern satisfies the predetermined condition (yes in S106), the reservation determination unit 12i determines that the reservation is the first reservation (S107). In S106, the information indicating the predicted traveling pattern is, for example, at least one of information indicating a predicted average speed, a predicted traveling distance, a predicted traveling time, and a predicted number of accelerations. The reservation determination unit 12i determines that the reservation is the first reservation when at least one of the information indicating the predicted average speed, the predicted travel distance, the predicted travel time, and the predicted number of accelerations is equal to or greater than a threshold value corresponding to each of them, in other words, when a corresponding condition (fourth condition) is satisfied.

When the reservation determination unit 12i determines the reservation as the first reservation in S107, the assignment unit 12j refers to the vehicle information database 13b and checks whether or not there is a vehicle 20 (hereinafter, referred to as a first vehicle) satisfying the second condition with high necessity of reduction among the assignable vacant vehicles 20 and the vehicles 20 satisfying the reservation conditions such as the size (level) of the vehicle, the driver, and the type of the vehicle (S108).

When the first vehicle is included in the plurality of vehicles 20 satisfying the reservation condition (yes in S108), the allocating unit 12j allocates the first vehicle to the reservation (S109). If there are a plurality of first vehicles satisfying the reservation condition in S109, the assignment unit 12j may assign the vehicle 20 with the highest reduction necessity (in other words, the vehicle 20 with the higher reduction necessity than the other vehicles 20) based on the level or the value of the parameter, or assign any one of the plurality of first vehicles 20 by another condition, for example. Then, the control unit 12 controls the communication unit 11 to transmit information indicating that the reservation of the vehicle 20 (first vehicle) has been successful to the terminal 30.

If no in S105, if no in S106, or if no in S108, the allocating unit 12j allocates the vehicle 20 that satisfies the reservation condition and is not the first vehicle to the reservation (S110). In this case, the control unit 12 controls the communication unit 11 to transmit information indicating that the reservation of the vehicle 20 (the vehicle 20 other than the first vehicle) is successful to the terminal 30. However, if there is no vehicle 20 that satisfies the reservation condition, the control unit 12 controls the communication unit 11 to transmit information indicating that there is no vehicle 20 that can be reserved to the terminal 30.

The order of determination in S102, S103, S104, and S105 (and S106) can be reversed.

As described above, in the present embodiment, in the server 10 (vehicle distribution device), the vehicle determination unit 12d determines the necessity of reducing the amount of the particulate trap 20c accumulated for each vehicle 20 based on the vehicle information corresponding to the vehicle 20. The reservation judging section 12i judges the reservation as a first reservation when reservation information corresponding to the reservation satisfies a first condition that a reduction in the particulate matter can be expected. Further, based on the reservation information, the distribution unit 12j can distribute the vehicle 20 having a higher necessity of reducing the amount of the accumulated particulate matter than the other vehicles 20 to the reservation when the reservation is the first reservation.

According to such a configuration and control, since a vehicle with a high necessity of reducing the amount of particulate matter stored in the particulate trap 20c can be distributed to the first reservation where the amount of particulate matter stored in the vehicle can be expected to be reduced, accumulation of particulate matter in the vehicle can be suppressed by distribution to the reserved vehicle. In addition, by suppressing accumulation of particulate matter in the vehicle, shortening of the vehicle life can be suppressed. Further, it is possible to suppress occurrence of a situation in which the distributed vehicles are concentrated on a specific vehicle and imbalance occurs in accumulation of the particulate matter.

[ second embodiment ]

In the first embodiment, the cause of the performance degradation of the internal combustion engine 20a is accumulation of particulate matter in the particulate trap 20 c. In contrast, in the second embodiment, the factor of the decrease in the performance of the internal combustion engine 20a is the deterioration of the oil properties (engine oil) in the internal combustion engine 20 a. The more the oil is diluted by water generated by condensation or the like in the internal combustion engine 20a, the higher the degree of deterioration. It is known that: the oil thus diluted with water is cloudy. In the second embodiment, the server, which is an example of the distribution device, is configured to execute the distribution control to the vehicle having a high necessity of reducing the degree of degradation of the first reserved distributed oil, which can predict the reduction (including the improvement) of the degree of degradation of the oil by making condensation or the like difficult.

The vehicle 20 according to the second embodiment is a vehicle that is equipped with a rotating electric machine as a drive source and that may operate an internal combustion engine intermittently, such as a hybrid vehicle or a plug-in hybrid vehicle. The sensor 24 can detect, for example, the temperature, humidity, and altitude as the outside environment information, and the rotation speed, load, water temperature of the cooling water, and oil temperature of the oil as the usage state of the internal combustion engine 20a, as various physical quantities related to the traveling of the vehicle 20 and the operation of the internal combustion engine 20 a. The control unit 22 of the vehicle 20 can calculate a calculated value relating to the degree of oil degradation based on the detection value detected by the sensor 24.

In the second embodiment, the driver information stored in the driver information database 13a of the server 10 as an example of the distribution device is the rotation speed, the degree of load, the frequency of intermittent operation, and the like of the internal combustion engine 20a as information indicating the driving performance of the driver. The driver information includes information related to a decrease in the degree of degradation of the oil. The information on the reduction in the degree of oil degradation is, for example, a classification indicating a driver who has a high possibility of performing driving with a reduced degree of oil degradation, a change amount in the degree of oil degradation caused by driving by the driver, or the like.

The vehicle information stored in the vehicle information database 13b may include, for example, the following information as information related to a decrease in the degree of degradation of the oil of each vehicle 20 calculated based on the detection value of the sensor 24. The information is, for example, a map, a table, a coefficient of a function, and the like set for each vehicle 20 or vehicle type for calculating the degree of degradation of the oil in each vehicle 20 based on the detection value, and the degree of degradation of the oil and the amount of change based on the detection value of the sensor 24. The vehicle information may include a detection value of the sensor 24 during the past travel of the vehicle 20 and a change with time of a calculated value based on the detection value. The vehicle information includes a classification, a level, and a value indicating the necessity of reducing the degree of oil degradation. The vehicle information may include a travel distance from the latest oil change and a brand using the oil. The storage unit 23 of each vehicle 20 may store a map, a table, a coefficient of a function, and the like for calculating the degree of degradation of oil and the amount of change from the detected values. The greater the amount of water in the oil, the greater the degree of degradation of the oil, and a map or the like in which the degree of degradation and the amount of water are associated with each other may be stored in the vehicle information database 13b and the storage unit 23 of each vehicle 20.

[ vehicle determination ]

In the second embodiment, the vehicle determination unit 12d determines the necessity of reducing the degree of deterioration of the oil in the internal combustion engine 20a of each vehicle 20. The necessity of reducing the degree of deterioration of the oil is one example of the necessity of suppressing the performance degradation of the internal combustion engine 20 a.

Fig. 7 is a flowchart showing a processing procedure of the determination of the decrease in the degree of oil degradation by the vehicle determination unit 12 d. The processing shown in fig. 7 can be executed at various timings, such as a point in time immediately after the vehicle 20 is returned, a point in time when the vehicle 20 becomes a candidate for allocation to a reservation, and a predetermined point in time that is periodically set.

Before the determination of the vehicle 20 by the vehicle determination unit 12d, the vehicle information acquisition unit 12a acquires the vehicle information corresponding to the vehicle 20 from at least one of the vehicle 20 and the vehicle information database 13b (S31).

Next, the vehicle determination unit 12d obtains the degree of oil degradation of the vehicle 20 based on the vehicle information obtained in S31 (S32). In S32, the vehicle determination unit 12d can perform calculation for estimating the degree of degradation of a fixed amount of oil by a predetermined calculation method based on the vehicle information acquired in S31. When the degree of degradation of the oil is acquired, the accuracy of the acquired degree of degradation is increased by considering information on the properties of the oil and the like when the oil replacement was previously performed.

Next, in S33, the vehicle determination unit 12d determines the necessity of reducing the degree of oil degradation for each vehicle 20 based on the obtained degree of oil degradation. For example, the vehicle determination unit 12d may determine the vehicle 20 as a vehicle with a high necessity of reducing the degree of oil degradation when the degree of oil degradation is equal to or greater than a predetermined threshold value, and may determine the vehicle 20 as a vehicle with a low necessity of reducing the degree of oil degradation when the degree of oil degradation is less than the predetermined threshold value. The predetermined threshold value can be set for each vehicle 20 or vehicle type, for example. The degree of degradation of the oil is equal to or greater than a predetermined threshold value, which is an example of the second condition.

After S32 or S33, the vehicle information update unit 12e rewrites the vehicle information of the vehicle information database 13b (S34).

[ driver judgment ]

In the second embodiment, the driver determination unit 12g determines whether or not the driver is a driver who has a high possibility of performing driving to reduce the degree of oil degradation. The flowchart showing the processing steps of the driver determination by the driver determination unit 12g is the same as that in the first embodiment shown in fig. 5. However, in the second embodiment, the detected value of the sensor 24 and the driver information to be rewritten when acquiring the driver information may be the same as or different from those in the first embodiment.

Further, the driver determination unit 12g determines whether or not the driver is a driver who has a high possibility of performing driving for reducing the degree of oil degradation based on the acquired driver information or the updated driver information. In this determination, the driver determination unit 12g determines that the driver is a driver who has a high possibility of performing driving with a reduced degree of degradation of the oil when the driver information indicating the driving performance of the driver satisfies a predetermined condition (an example of a third condition) that can be expected to reduce the degree of degradation of the oil by driving. Hereinafter, in the second embodiment, a driver who has a high possibility of performing driving with a reduced degree of oil degradation is referred to as a first driver.

For example, the driver determination unit 12g may determine that the driver is the first driver when the average speed is equal to or higher than the corresponding threshold speed due to a high frequency of using the expressway, or the like. In addition, for example, when the travel distance is equal to or greater than the corresponding threshold distance, the driver determination unit 12g continues traveling to a degree that the degradation is reduced (for example, to a degree that the oil temperature of the oil is increased to 80 ℃. For example, the driver determination unit 12g may determine the driver as the first driver when the average load and the total load are equal to or greater than the corresponding threshold load due to traveling with a high load applied to the internal combustion engine 20a, such as traveling on an uphill road or traveling with a high acceleration frequency. When the driver first uses the shared vehicle system 1, the information used for the determination may be estimated from information such as the destination, the number of people using the vehicle, and the weather included in the reservation information. That is, a part or all of the driver information for determining whether a certain driver is the first driver may be included in the reservation information.

[ reservation determination and allocation of vehicles to reservations ]

In the second embodiment, the reservation judging unit 12i judges whether or not the reservation satisfies a condition (an example of the first condition) for predicting a decrease in the degree of degradation of the oil based on the reservation information acquired from the terminal 30. The traveling pattern prediction unit 12h predicts the traveling pattern of the vehicle 20 based on the reservation information. The assigning unit 12j selects a vehicle 20 satisfying a condition (reservation condition) specified by the reservation information from among the vehicles 20 managed by the shared automobile system 1, and assigns the vehicle 20 to the reservation. In the following, a reservation for which reduction of the degree of oil degradation can be predicted, that is, a reservation for which there is a high possibility of driving for reducing the degree of oil degradation is referred to as a first reservation.

The flowchart showing the processing steps of the reservation determination by the reservation determination unit 12i and the allocation of the vehicle 20 to the reservation by the allocation unit 12j is the same as that in the case of the first embodiment shown in fig. 6. The fourth condition also includes a case where the predicted load of the internal combustion engine is equal to or greater than the threshold value.

As described above, in the present embodiment, in the server 10 (vehicle distribution device), the vehicle determination unit 12d determines the necessity of reducing the degree of degradation of the oil in the internal combustion engine 20a for each vehicle 20 based on the vehicle information corresponding to the vehicle 20. The reservation determination unit 12i determines that the reservation is the first reservation when the reservation information corresponding to the reservation satisfies a first condition that the degradation degree of the oil can be predicted to decrease. Further, based on the reservation information, the distribution unit 12j can distribute the vehicle 20 having a higher necessity of reducing the degree of degradation of the oil than the other vehicles 20 to the reservation when the reservation is the first reservation.

According to such a configuration and control, since a vehicle with a high necessity of reducing the degree of degradation of the oil can be distributed to the first reserved distribution where the degree of degradation of the oil can be expected to be reduced, it is possible to suppress degradation of the oil in the internal combustion engine of the vehicle by distribution to the reserved vehicle. Further, by suppressing degradation of the oil, shortening of the vehicle life can be suppressed. Further, it is possible to suppress occurrence of a situation in which the deployed vehicles are concentrated on a specific vehicle and an imbalance occurs in the degree of oil degradation.

When it is estimated that the water content in the oil exceeds the predetermined threshold value, the control unit 12 of the server 10 and the control unit 22 of the vehicle 20 may urge the driver to change the oil via the in-vehicle information device such as a car navigation system or the terminal 30 regardless of the estimation result of the degree of degradation. Alternatively, the driver may be urged to drive to reduce the degree of oil degradation (e.g., to drive continuously to some extent).

[ third embodiment ]

Fig. 8 is a block diagram of the control unit 12 and the storage unit 13 of the server 10A according to the present embodiment. As shown in fig. 8, in the present embodiment, the control unit 12 includes a learning unit 12 k. The driver determination unit 12g determines the driver using the learned model generated by the learning unit 12 k. The configuration of the shared automobile system 1 is the same as that of the first embodiment, except that the server 10A is provided instead of the server 10.

The learning unit 12k performs machine learning based on an input/output data set as part of the driver information. The learning unit 12k writes the learned model as the result of learning into the learned model storage unit 13c of the storage unit 13. The learning unit 12k can write the latest learned model at a predetermined timing into the learned model storage unit 13c independently of the neural network that is learning. The writing of the learned model into the learned model storage unit 13c may be updating of deleting the old learned model and writing the latest learned model, or accumulating of leaving a part or all of the old learned model and writing the latest learned model.

The storage unit 13 includes a learned model storage unit 13c and a learned data storage unit 13d in addition to the driver information database 13a and the vehicle information database 13 b. The learned model storage unit 13c stores the learned model so as to be retrievable. The learned model storage unit 13c initially stores the learned model in the initial state. The learned model is a learned model generated based on deep learning using a neural network. The term "store the learned model" means to store information such as network parameters and arithmetic algorithms in the learned model. The learned model is stored in a manner that establishes an association with the driver information. It should be noted that the learned model may also be stored in a manner of being further associated with the vehicle information. In addition, the learning data storage unit 13d stores learning data. The learning data will be described later.

Here, deep learning using a neural network will be described as a specific example of machine learning. Fig. 9 is a diagram schematically showing the configuration of the neural network learned by the learning unit 12 k. As shown in fig. 9, the neural network 100 is a feedforward neural network, and includes an input layer 101, an intermediate layer 102, and an output layer 103. The input layer 101 is composed of a plurality of nodes, and different input parameters are input to the respective nodes. The intermediate layer 102 is input with an output from the input layer 101. The intermediate layer 102 has a multilayer structure including a layer configured by a plurality of nodes that receive input from the input layer 101. The output layer 103 receives the output from the intermediate layer 102 and outputs the output parameters. Machine learning using a neural network in which the middle layer 102 has a multilayer structure is called deep learning.

Fig. 10 is a diagram illustrating an outline of input and output at a node included in the neural network 100. In fig. 10, a part of input and output of data in the input layer 101 having I nodes, the first intermediate layer 121 having J nodes, and the second intermediate layer 122 having K nodes in the neural network 100 is schematically shown (I, J, K is a positive integer). Input parameter x is input to the ith node from the upper side of input layer 101_i(I ═ 1, 2, …, I). Hereinafter, a set of all input parameters is referred to as "input parameters { x_i}”。

Each node of the input layer 101 outputs a signal having a value obtained by multiplying the input parameter by a predetermined weight to each node of the adjacent first intermediate layer 121. For example, the ith node from the upper side of the input layer 101 has a pair input parameter x for the jth (J ═ 1, 2, …, J) node output from the upper side of the first intermediate layer 121_iMultiplying by a weight α_ijTo obtain a value alpha_ijx_iOf the signal of (1). The input to the jth node from the upper side of the first intermediate layer 121 is obtained by adding a predetermined offset b to the output from each node of the input layer 101⁽¹⁾ _jThe obtained value sigma_i＝1～Iα_ijx_i+b⁽¹⁾ _j. Here, the first item ∑_i＝1～IMeaning that I is the sum of 1, 2, …, I.

The output value y of the jth node from the upper side of the first intermediate layer 121_jAs an input value Σ from the input layer 101 to the node_i＝1～Iα_ijx_i+b⁽¹⁾ _jIs expressed as y_j＝S(Σ_i＝1～Iα_ijx_i+b⁽¹⁾ _j). This function S is called an activation function. As a particular activityExamples of the linearization function include a Sigmoid function s (u) ═ 1/{1+ exp (-u) }, a modified linear function (ReLU) s (u) ═ max (0, u), and the like. Often, a nonlinear function is used for the activation function.

Each node of the first intermediate layer 121 outputs a signal having a value obtained by multiplying the input parameter by a predetermined weight to each node of the adjacent second intermediate layer 122. For example, the jth node from the upper side of the first intermediate layer 121 has a pair input value y to the kth (K ═ 1, 2, …, K) node output from the upper side of the second intermediate layer 122_jMultiplying by a weight beta_jkTo obtain a value beta_jky_jOf the signal of (1). The input to the kth node from the upper side of the second intermediate layer 122 is obtained by adding a predetermined offset b to the total output from each node of the first intermediate layer 121⁽²⁾ _kThe obtained value sigma_j＝1～Jβ_jky_j+b⁽²⁾ _k. Here, the first item ∑_j＝1～JMeaning that J is the sum of 1, 2, …, J.

Output value z of the kth node from the upper side of the second intermediate layer 122_kUsing the input value Σ from the first intermediate layer 121 to the node_j＝1～Jβ_jky_j+b⁽²⁾ _kIs expressed as z as an activation function of the variable_k＝S(Σ_j＝1～Jβ_jky_j+b⁽²⁾ _k)。

In this way, by repeating the operations in the forward direction from the input layer 101 side to the output layer 103 side, one output parameter Y is finally output from the output layer 103. Hereinafter, the weights and biases included in the neural network 100 are collectively referred to as network parameters w. The network parameter w is a vector having all the weights and offsets of the neural network 100 as components.

The learning unit 12k performs a learning operation based on the input parameter { x }_iThe calculated output parameter Y and input parameter { x } are input to the neural network 100_iTogether constitute an output parameter (target output) Y of the input-output data set₀To update the operation of the network parameter w. Specifically, by performing a process for combining 2 output parameters Y and Y₀Is calculated to minimize the errorAnd updating the network parameter w. At this time, a random gradient descent method is often used. The parameter { x ] is input as follows_iAnd set of output parameters Y ({ x)_i}, Y) are collectively referred to as "learning data".

The outline of the random gradient descent method is described below. The stochastic gradient descent method is based on using 2 output parameters Y and Y₀A gradient determined by a defined error function E (w) with respect to the differentiation of the components of the network parameter w

And updating the network parameter w in a minimized mode. The error function is composed of, for example, the output parameter Y of the learning data and the output parameter Y of the input-output data set₀Square error of | Y-Y₀|²And (4) defining. In addition, the gradient

Is a derivative, i.e. a derivative, with an error function E (w) related to the composition of the network parameter w

(here, I is 1 to I, J is 1 to J, and K is 1 to K).

In the stochastic gradient descent method, the network parameter w is sequentially updated to the network parameter w using a predetermined learning rate η that is automatically or manually determined

Note that the learning rate η may be changed during learning. In the case of the more general stochastic gradient descent method, the error function e (w) is defined by random extraction from samples containing the entire learning data. The number of pieces of learning data extracted at this time is not limited to 1, and may be a part of the learning data stored in the learning data storage unit 13 d.

As means for effecting gradients efficiently

As a method of calculating (2), an error back propagation method is known. Error back propagation method is to calculate the learning data ({ x)_iY) is output based on the target in the output layer₀And error of the output parameter Y, and gradient like output layer → intermediate layer → input layer

Against a retrospective calculation method. The learning unit 12k calculates the gradient by using an error back propagation method

After all the components are added, the gradient calculated by using

The network parameter w is updated using the random gradient descent method described above.

The learning unit 12k extracts driver information used for machine learning from the driver information stored in the driver information database 13 a. The input parameters for machine learning are information indicating past travel performance of the driver, such as an average speed, a travel distance, a travel time, the number of accelerations equal to or higher than a predetermined acceleration, and an average acceleration during acceleration, for example. The output parameter of the machine learning is, for example, a division indicating whether or not the driver is the first driver, and a change amount of the particulate matter per unit length of a travel distance or per unit time of a travel time by the driving of the driver. The amount of change in the particulate matter is, for example, positive for an increase and negative for a decrease, and a smaller value indicates a larger amount of reduction in the accumulated particulate matter. The input parameters may include attribute information of the driver, such as the sex, age, region of residence, occupation, and interest of the driver.

The learning by the learning unit 12k is performed at a predetermined timing (for example, every time the driver information is added or updated). As a result, the learned model associated with the driver information is accumulated in the learned model storage unit 13 c. The learning unit 12k may store the generated learned model in the learned model storage unit 13c in association with the vehicle information. The learning unit 12k may update the learned model generated in the past with a new learned model having a high degree of matching with the driver information associated with the learned model. The learning unit 12k may generate a new learned model by combining and averaging a plurality of learned models in which the associated driver information is close to each other. In the case of averaging the learned models, the network parameters w in the plurality of learned models can be averaged for each node. The learning unit 12k may change the number of nodes. The learning unit 12k may merge or update the plurality of learned models with reference to the vehicle information. In this way, the learned models generated in the learned model storage unit 13c are accumulated, updated, merged, averaged, and stored.

In such a configuration, when determining the driver, the driver determination unit 12g selects at least 1 learned model associated with the driver information having the highest degree of matching from the learned model storage unit 13c based on the driver information associated with the identification information of the driver to be determined.

Then, the driver determination unit 12g obtains, as the output parameter, the amount of change in the particulate matter per unit length of the travel distance or the travel time due to the driving of the driver, which indicates whether or not the driver is the first driver, by inputting the driver information as the input parameter to the selected learned model. By using the learned model, the possibility of reduction of particulate matter caused by the driving of the driver can be estimated with high accuracy from a stage at which driver information indicating the performance of the driving of the driver is relatively small.

In the third embodiment described above, the possibility of reduction of the particulate matter due to the driving by the driver is estimated as in the first embodiment, but the possibility of reduction of the degree of deterioration of the oil due to the driving by the driver may be estimated as in the second embodiment.

Although the embodiments of the present invention have been described above, the above embodiments are examples and are not intended to limit the scope of the present invention. The above embodiments can be implemented in other various ways, and various omissions, substitutions, combinations, and changes can be made without departing from the spirit of the invention. Further, specifications such as the structure and shape (structure, type, pattern, number, arrangement, and the like) can be appropriately changed and implemented.

For example, in the above-described embodiment, one server has all the functions as the vehicle distribution device, but the present invention is not limited to this, and each function may be shared by a plurality of computers connected so as to be able to communicate via a network. The storage device may be connected to a device that executes each process so as to be able to communicate with the device via a network.

In addition, when the driver information is included in the reservation information, the reservation determination unit may determine that the driver is the first driver and the first reservation is determined with respect to the reservation when the driver information satisfies the third condition. The driver information included in the reservation information is, for example, information indicating the use or non-use of a scheduled route point, a scheduled travel route, an expressway, attribute information of the driver, and the like.

The present invention is also applicable to a system for assigning any one of a plurality of vehicles for a reservation, such as a rental car system, in addition to a shared car system.

Claims

1. A vehicle distribution device is provided with:

a vehicle determination unit that determines, for each vehicle, a necessity to suppress a decrease in performance of the internal combustion engine based on vehicle information corresponding to the vehicle;

a reservation determination unit that determines a reservation as a first reservation when reservation information corresponding to a reservation of a borrowed vehicle satisfies a first condition that can suppress a decrease in performance; and

a distribution section that distributes a vehicle to the reservation based on the reservation information,

the allocation unit may allocate, to the reservation, a vehicle satisfying a second condition that is high in necessity of suppressing the decrease in the performance or a vehicle having a higher necessity of suppressing the decrease in the performance than another vehicle, when the reservation is the first reservation.

2. The vehicle distribution apparatus according to claim 1,

the necessity of suppressing the performance of the internal combustion engine from being degraded is a necessity of reducing particulate matter accumulated in a particulate trap provided in an exhaust path of the internal combustion engine.

3. The vehicle distribution apparatus according to claim 1,

the necessity of suppressing the decline in the performance of the internal combustion engine is a necessity of reducing the degree of deterioration of oil in the internal combustion engine.

4. The vehicle distribution device according to any one of claims 1 to 3,

a driver determination unit configured to determine the driver as the first driver when driver information corresponding to the driver satisfies a third condition that suppresses the performance degradation,

the reservation determination unit determines that the reservation is the first reservation when the reservation is a reservation for the first driver to drive the vehicle.

5. The vehicle distribution apparatus according to claim 4,

6. The vehicle distribution device according to any one of claims 1 to 3,

the reservation determination unit determines the driver as the first driver when driver information corresponding to the driver included in the reservation information satisfies a third condition that can suppress the performance degradation,

7. The vehicle distribution device according to any one of claims 1 to 6,

the reservation determination unit determines whether or not the reservation is the first reservation based on predetermined path information included in the reservation information.

8. The vehicle distribution apparatus of claim 7,

the reservation determination unit determines that the reservation is the first reservation when the planned route information includes a predetermined road as a planned travel route or a point separated by a predetermined distance from a reference position as a planned route point.

9. The vehicle distribution device according to any one of claims 1 to 8,

the reservation determination unit predicts a traveling pattern of the vehicle based on the reservation information, and determines the reservation as the first reservation when information indicating the traveling pattern satisfies a fourth condition that can suppress the performance degradation.

10. The vehicle distribution apparatus of claim 8,

the reservation determination unit predicts a traveling mode of the vehicle based on the reservation information and driver information corresponding to a driver who drives the vehicle in the reservation.

11. The vehicle distribution apparatus of claim 9 or 10,

the information indicating the running form is at least one of information indicating a predicted average speed, information indicating a predicted running distance, information indicating a predicted running time, a predicted load of the internal combustion engine, and information indicating a predicted number of accelerations.

12. A vehicle distribution method is a computer-implemented vehicle distribution method, and comprises the following steps:

determining, for each vehicle, a necessity of suppressing a decrease in performance of the internal combustion engine based on vehicle information corresponding to the vehicle read out from the storage unit;

a step of determining that the reservation is a first reservation when reservation information corresponding to the reservation by the vehicle satisfies a first condition that can suppress the performance degradation; and

a step of allocating a vehicle to the reservation based on the reservation information,

in the step of allocating a vehicle to the reservation, when the reservation is the first reservation, a vehicle satisfying a second condition that is high in the necessity of suppressing the decrease in the performance or a vehicle having a higher necessity of suppressing the decrease in the performance than other vehicles may be allocated to the reservation.

13. A recording medium having a program recorded thereon for causing a computer to function as a vehicle determination unit, a reservation determination unit, and a distribution unit,

the vehicle determination section determines necessity of suppressing a decrease in performance of the internal combustion engine for each vehicle based on vehicle information corresponding to the vehicle,

the reservation determination unit determines that the reservation is the first reservation when reservation information corresponding to the reservation of the borrowed vehicle satisfies a first condition that suppresses the performance degradation,

the allocating section allocates a vehicle to the reservation based on the reservation information,

wherein the allocation unit is configured to, when the reservation is the first reservation, allocate to the reservation a vehicle satisfying a second condition that is high in necessity of suppressing the decrease in the performance or a vehicle having a higher necessity of suppressing the decrease in the performance than other vehicles.